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Theme Issue: AI-powered Security and privacy in Smart E-Health

With the growing volume of aged who have long-term chronic diseases, people have been focusing on the effective and efficient disease prevention with limited medical infrastructure and services. To tackle this issue, a feasible way is non-stop surveillance of patients’ daily activities and physical conditions to aid quick and accurate disease diagnoses and treatment. In this situation, information technology (IT) has offered a promising way to record the big volume of diagnosis and treatment data generated in daily clinical activities, which benefits us significantly in developing various E-Health applications to satisfy patients’ functional and non-functional health requirements.
However, the big health data collected by IT-based medical equipment place a heavy burden on the secure data management and value-added knowledge mining. How to integrate and analyze the big health data from multiple sources in an accurate, secure and privacy-preserving manner is still a fundamental challenge. Fortunately, Artificial Intelligence (AI) has recently emerged as one of the key technologies to achieve secure data transmission and privacy-aware knowledge extraction. However, the adaptation of AI-based security and privacy-protection solutions are highly demanded to achieve their full potentials in smart E-Health applications.
In this special issue, we look for significant findings in tackling new security and privacy issues that challenge AI-based smart E-Health applications. Specifically, we solicit novel contributions on secure and privacy-aware AI applications in E-Health from a variety of perspectives, e.g., architecture, models, data, algorithms, etc.
Potential topics include, but are not limited to, the following:
- AI-powered big data analytics for E-Health
- Machine learning and reinforcement learning for E-Health
- Intelligent data sampling and fusion in E-Health
- AI algorithms, models and framework for E-Health
- Smart control system for E-Health applications
- Security, trust and privacy in E-Health
- Cross-platform medical data sharing and integration
- Industry 4.0 and intelligent manufacture for E-Health
- Software, hardware and infrastructure supporting E-Health
- Economy, laws and ethics for E-Health